Contents


Desktop GIS

QGIS

QGIS (formerly Quantum GIS) is the most complete GIS. Functions from GRASS, SAGA and GDAL (see below) can be used via QGIS’s processing toolbox. Additionally, it offers a Python interface.

GRASS GIS

GRASS is one of/the oldest GIS out there. Besides offering a huge toolbox, it provides full 3D support and time series support.

SAGA GIS

SAGA GIS (System for Automated Geoscientific Analysis) is an amazing GIS toolbox that is developed for one purpose: automating geoscience analyses. Besides offering a ridiculous amount of rock-stable processing and analyses functions (incl. proper references given), it is a great tool for (manual/exploratory) GIS file type/data format conversion. Most repositories of Linux distributions contain outdated versions of SAGA. hence, newer versions have to be compiled for Linux manually.

QMapShack

QMapShack (formerly QLandkarte GT) is a useful tool to visualize GPS tracks or plan them for usage on a GPS device.

gvSIG

gvSIG was originally developed for/by the Generalitat Valenciana is aimed to be a fully featured GIS and a mobile version is available as well. IMHO resources (if any left) should be moved to help with QGIS since gvSIG never performed the way it shoulduntun.

OpenJUMP

OpenJUMP seems to be written in JAVA and is (IMHO) super slow.

(Relational) Database Management Systems (RDBMS)

There a lot of filetypes/databases for geospatial purposes. However, there are only two databases systems that are designed as real databases. Additionally, GeoPackage could be controlled using SpatiaLite.

PostGIS

Technically speaking, PostGIS is an extension to PostgreSQL. Whenever working with PostGIS, I recommend to estimate if operations run faster on the database server or on the workstation/processing server.

SpatiaLite

SpatiaLite is an extension to SQLite and therefore is a DBMS that can be used for file databases.

Geospatial packages for programming languages

GDAL

GDAL is used by basically all GIS applications mentioned here to manage a lot of their file I/O since it supports almost every format.

Julia

GeoStats.jl

GeoStats.jl offers functions for spatial interpolation and statistical modeling (Kriging).

R

geoR

geoR is a package for geostatistical data analysis with R. It basically covers various Kriging methods (incl. Bayesian Kriging).

geoRglm

geoRglm is similar to geoR but focuses on generalized linear (spatial) models.

gstat

gstat offers Kriging methods (incl. spatio-temporal).

RGeostats

RGeostats and R2l are other packages for spatial statistics.

spacetime

spacetime contains classes and methods for spatio-temporal data .

Python

GeoPandas

GeoPandas is a pandas-like dataframe to store/handle geodata in Python. It provides rudimentary functions for geometric manipulation.

HPGL

HPGL offers geostats tools for Python.

pyGeoStatistics

pyGeoStatistics offers a variety of tools for geostats.

PyKrige

PyKrige offers various kinds of Kriging.

WhiteboxTools

Whiteboxtools offers geospatial analyses functions.